{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 第0节：Matplotlib绘图函数\n",
    "Matplotlib提供了16种不同图象的绘制函数\n",
    "\n",
    "以下提供一些例子\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 第1节：饼图\n",
    "函数：plt.pie(data, explode)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "labels = 'A', 'B', 'C', 'D'  # 标签\n",
    "sizes = [15, 30, 45, 10]  # 每一个区域的比例\n",
    "explode = (0, 0.1, 0, 0)  # 每一块是否突出来\n",
    "\n",
    "plt.pie(sizes, explode=explode, labels=labels,\n",
    "        autopct='%1.1f%%', shadow=False, startangle=90)\n",
    "# autopct:百分数的呈现形式\n",
    "# shadow:在饼图下面画一个阴影。默认值：False，即不画阴影\n",
    "# startangle:起始绘制角度,默认是从x轴正方向逆时针画起,如设定90则从y轴正方向画起\n",
    "\n",
    "plt.axis('equal')  # 该行代码使饼图长宽相等\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 第2节：直方图\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "np.random.seed(0)\n",
    "mu, sigma = 100, 20\n",
    "a = np.random.normal(mu, sigma, size=100)#生成一组服从正态分布的随机数\n",
    "\n",
    "#bin：总共有几条条状图\n",
    "plt.hist(a, 20, density=True, histtype='stepfilled', facecolor='b', alpha=0.75)\n",
    "plt.title('Histogram')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# 第3节：极坐标图（了解）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "N = 10\n",
    "theta = np.linspace(0, 2*np.pi, N, endpoint=False)\n",
    "radii = 10*np.random.rand(N)\n",
    "width = np.pi/2*np.random.rand(N)\n",
    "\n",
    "ax = plt.subplot(111, projection='polar')\n",
    "bars = ax.bar(theta, radii, width=width, bottom=0.0)\n",
    "\n",
    "for r, bar in zip(radii, bars):\n",
    "    bar.set_facecolor(plt.cm.viridis(r/10.))\n",
    "    bar.set_alpha(0.5)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "# 第4节：散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAD4CAYAAADxeG0DAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAeqUlEQVR4nO3df2wexZkH8O/zvrZjB+eEROI4aXATk7iAQpVgK4AretBWOqiqIihI7VW0PcL5Tippi6pTW1Vc/0AnTkIHOaA6Ck1ouVatKnHpndoiSiUqCm5Q7QP1AmnfuAQ4n/3GgaoFYzv263fuD/uFN69333d/zO7OzH4/EhLxj915d9ezM888MyNKKRARkb0KWReAiIjiYUVORGQ5VuRERJZjRU5EZDlW5ERElmvL4qQbN25U27dvz+LURETWGh8ff10ptanx65lU5Nu3b8fY2FgWpyYispaIvOr1dYZWiIgsx4qciMhyrMiJiCyXSYyciCiMpaUlTE5OYmFhIeuipKKzsxPbtm1De3t7oJ9nRU5ExpucnMSGDRuwfft2iEjWxUmUUgpvvPEGJicnsWPHjkC/w9AK5cpspYLS3BxmK5Wsi0IhLCws4LzzznO+EgcAEcF5550XqvfBFjnlQqVaxe0TEzhULqMogmWlsL+3F/fu3Im2AtszNshDJV4T9rOyIqdcuH1iAofLZcxXq+987XC5DAC4f2Agq2I1NVupYGpxEVs7OtDdxj9V8semCDlvtlLBoXIZc3WVOADMVas4VC4bF2apVKs4UCqhZ3QUg+Pj6BkdxYFSCZWG8lO6isUi9uzZg927d+Omm27C3Nxc058fHh5uecyDBw+2PE4QrMjJeVOLiyj6dFWLIphaXEy5RM3V9x5ml5cxX63icLmM2ycmsi6aVXSPh3R1deGFF17AsWPH0NHRgQcffLDpz4+OjrY8JityooC2dnRg2WcnrGWlsLWjI+US+bOt92CiNHo0V155JSZWX6z33HMPdu/ejd27d+PgwYPv/Ex3dzcA4Je//CWuuuoq3Hjjjbjwwgvx6U9/Gkop3HfffZiamsLVV1+Nq6++OlZ5WJGT87rb2rC/txfrGwY11xcK2N/ba1T82bbeg4mS7tFUKhU8/vjjuOSSSzA+Po5HHnkEzz33HI4ePYqHH34Yzz///Jrfef7553Hw4EG89NJLePnll/Hss8/iC1/4ArZu3YqnnnoKTz31VKwysSKnXLh3507c0tuLrkIB3cUiugoF3LKatWISm3oPJkqyRzM/P489e/ZgaGgIfX192L9/P5555hlcf/31OOecc9Dd3Y0bbrgBv/rVr9b87r59+7Bt2zYUCgXs2bMHr7zySuRyeDGnKUKUoLZCAfcPDOCu/n6jM0FqvYfDDZXR+tUXj4llNkmQHs1AxGtYi5HXC7p5/bp1694tR7GIiuYQGVvklCvdbW0YWL8e3W1txk4OsqX3YKK0ezQf/OAH8eMf/xhzc3N4++23ceTIEVx55ZWBf3/Dhg146623YpeDr3fKHdMnB9nSezBR2j2aSy+9FJ/73Oewb98+AMCtt96KvXv3Bv79kZERXHvttdiyZUusOLkE7RroNDQ0pLixBGXlQKnk+4du6uSgvDt+/DguuuiiQD9r+os6KK/PLCLjSqmhxp+N/XoSkfMBPAqgF0AVwENKqX+Ne1yiJNQGw+Z9BsPu6u9n69dyeezR6Hg9VQB8WSl1EYDLAXxeRC7WcFwi7fKS3mdq/D9N9eMhrov9CZVS0wCmV///LRE5DuA9AF6Ke2wi3VxP73MlrOBFKZWbhbPChry13lkR2Q5gL4DndB6XSBebJgdF4er0/s7OTrzxxhuhKzgb1dYj7+zsDPw72p5aEekG8BiALyml3vT4/giAEQDo6+vTdVqi0GppfPWtVhfS+1yO/2/btg2Tk5M4ffp01kVJRW2HoKC0ZK2ISDuAnwB4Qil1T6ufZ9YKmcC1ZWJLc3MYHB/H7PLymu91F4sYHxzEwPr1GZSMdEkya0UAHAJwPEglTmSK7ra2yLP8TOR6/J/86YiRfwDAzQA+JCIvrP73UQ3HJaIQXI//kz8dWSvPAMjHUDKR4VyN/1NzfEUTOSSPk2GIFTmRk1yL/1Nzds8QICIiVuRERLZjRU5W4loiRO9iEI2s4vJaIkRRsSInq9SvJVJzuFwGAK4lTrnFJgxZI8mNdYlsxoqcrJGXtcSJwrKuIucgV35xLREib9ZU5JVqFQdKJfSMjmJwfBw9o6M4UCqh0tDNJnflYS0RNlQoCmuefA5yEeDuWiLMxqE4tKxHHlbY9chnKxX0jI6uWTAfALoKBcwMDzvRGqPgXFtL/ECphMMNA7nrCwXc0tvLhgq9w289cite9RzkokYubazLbByKy4qKnINc5DI2VCguKyryPAxyUX6xoUJxWVGRAyuDXLf09qKrUEB3sYiu1fih7YNcRGyoUFzWPCFcMJ9c5mo2DqXDiqwVorxwLRsnrLx//lb8slZ4pYgMktedfZhHH0/+nhgiMg4n/MXDVx0RODU+S8yjj48tcso1dumzFySPPo/hpjB4dQhAfgeZ2KXPHvPo42OTI+dcWlUybHiEXXozMI8+Pl6hnHOhRRo1PMIuvTmYRx8Pn9Icq7VIG1eVrLVI7+rvt6I1FPVlpLtL72J4Kq3PxAl/8TC0kmMuLNYUJzyiq0vvUniqJqvP5NKqlmni1coxFwaZ4oZHdHTpXQhPNXLxM7mMLXLDpJnP7MIgU9yXUa1LPzM8jPHBQcwMD+P+gYHAqYcuDpi6+Jlcp6UiF5HDIjIjIsd0HC+PsurK2r6qpK6XUdQuvQvhqUYufibX6WpyfQfAAwAe1XS83MmqK+vCIFOWGQ8uhKcaufiZXKelRa6UehrAH3UcK49M6MraPMgUNzwShwvhqUYufibXpXZHRGQEwAgA9PX1pXVaKzCfWY+sVg50MQfaxc/kMm3rkYvIdgA/UUrtbvWzXI/8bLOVCnpGR9fkcwNAV6GAmeFhtoIswDxySprfeuTMWjEAu7JusDk85cfFz+Qi3h1DsCtLRFFpqchF5AcArgKwUUQmAXxDKXVIx7HzwoXsESLKhpaaQin1KR3Hofxu9UWtMV5Nfvg0EBmOm19QK6zIiQzHdU+oFb7OKTSv9WBM3fMyjXIleQ4TJouR+dgid1QS8VSvLv7fbN4MAHjk1Cmjuv1phCPSOMeJ+Xl4TxXjZDF6F58AxyRZuXh18R+anl45b93PmdDtTyMckeQ5avfx2+UyFnwWTuO6J1TD0EoCsgwz1Fcus8vLmK9Wcbhcxu0TE7GO69fFr+DsShwI3+3Xfb3SCEckfY7affSrxDlZjOqxItco651ikqxcmq0H4yXIcqdJXa80lmFN8hx+97GmU8R3spipYxWULL7ONco6uyDJxbeaLW3qJUi3P6nrlcYyrEmeo9l9XF8o4Jm9e7F3w4azvs4UxXzjHdbEhOyCJCsXv/Vg2rC2NRCk25/k9Upj7Zokz9HsPioAu7q61nw9qZAa2YEVuSYm7KoSpHKJ0/X22k1oZMsWjGzZEnqHoaSvl1dZb9i4EXfu2BHruK3OoWN9nLAvCRMaEZQtbcvYhuHiMramLEXr18W++4IL8A9/+EOkrndjKqNXamPYdMe0rteflpZw24kTeOz0abQVComEHNJK9fQrd2luDoPj45hdXl5znO5iEeODgxhYv15LuYLgUgLJ8VvGlldZk1or6nBDy2j9aistrQfab/GtA6VS6Hh0s8qksWIIu0ZMWtfrjpMnceT117GgFLBa0eket0hifZwwi6iZsjUb4/TZ4dXVyKSNjOvXkY7a9U467pr09XIh5BBkPXBT1rNnnD47DK0kwLSuZZSud5qhoqSuV5DPvbWjI9F7ldazkHVr2JTQousYWkmRaUvRRul6R0lljFppJXW9Wn3uf3ntNfz7zEwiFV/aFWuQUEySLxXuO5stXtkciBKPDlP5Z90a9NPsc1/Q2YnvzcwklvOf1ZwCr5diGvfHlDh9XjFGnhNh49Fh4q4mx0a9PvfNmzfjxPx8YrFz02Lzadyf2vPS5dEq39nZiU4OdiaKMfKcCdO9DtKSsyU2Wv+5pxYXE03XMykdMM37U6lWcenYGP5nbu6sr9d6flw7PT7GyAlAuHh0kLirLbHR+s+9FUg0DKArzKAjpp3m/VmoVjGxsLDm67WeyF39/Ua81F3E/g611CwFzsbYaNLpenGPr3MxsTTvjwmzm/OKFTnFYkoOc1hJ57DHOb7OmHaa98fEl3peVoNkjJxiMzVrJYik87xNWLogzftTm0HslR2VZozc5meyGb8YOSty0sa0iVA20jVQqmM9nChMqUBNeaHoxoqcjMUXwLvitshNqUizvKe2ZFJF4VeR29vHoMzoijtmvaOSieLGtE3J6Q+yRkxS8jjoaudriTKhu7XnNfvx29PTWKxW8a0LL9RZ9FToaoXWBkTrr3OzgdLaef+iWMShhusJ5C/9z8RB16S5f1cz5lLYQOe089rsx8ZKZ0EpPFQuQ0TwwK5dVgxM6X7BBV3CtvG8S9Uqqj4VmEk5/UkzZUnpNLn3iQxhSqxSF7+KN2prr9Vmzt89dQrtIpFeEGm/OJNaV6XV5C2v8/pxtSXqJ2yvxnasyBOS9UbMuumeIdhqM+eFkC+IrF6cul9wcc/rxeWWqJ8wG3O4wL6moQVMWzRJB91xx1r3t7NJqzzMwFRWg3xZDaw1O2+7CNaJZL65iQmyHHRNk5aKXESuEZHfi8iEiHxVxzFt5uKoeRIzBO/duROf2bzZ9/tBXxBZvjizGlhrdt42Ebxy+eUYHxzEzPAw7h8YsDKcR8HFvrsiUgTwTQDXArgYwKdE5OK4x7WZq6Pmuqe1txUK+NaFF+LvtmxZs8xpmBdE2Bdns/TJsKmVWS1R0Oq8vevWrWmJ5mW6eh7peMr2AZhQSr0MACLyQwDXAXhJw7Gt5OqoeVJxxwd27UK7SOSBqaAvzmZxdACRY+xZDawFPa9rA++0VuyZnSJyI4BrlFK3rv77ZgCXKaVua/i5EQAjANDX1zf46quvxjqv6fjHE15jxkmYDJQgU7Kb/QyA2FO6s0o1bXVeV6er51FiU/RF5CYAf9VQke9TSh3w+508TdF3KY/cj+7PGOUl2Op3Wk3bVkphweNvoatQwMuXXYY3l5eNWVgr7LGjTFfPw3NroyQ3lpgEcH7dv7cBmNJwXCeYthGzTkn1OqKkbvqFfWYrFUwtLODt5WXfOLoAEBHAoyKvKIXtR4+ivVCwcoPm186c8V3ywCttlD1JO+moYX4DYJeI7ADwfwA+CeCvNRyXDJdErnzcvOzai7O2jkutQqpUq1jy6X0qAH4909rvnFldjdC2DZrvm5zEks/3vAbeXZv/kBexX7FKqQqA2wA8AeA4gB8ppV6Me1wyW1Ipf7pSNxvzyheUgmBty6WW5XHrli1rMkC82LRB82ylgkdPnfL9/s09PWuyWlyb/5AXWvr8SqmfAfiZjmORHZLaC1JH6qZfq74CoIiV2LBflsc7LXilsFyterZmw34+r3hzGntptpo09MVt2wL/fJ7WarER7wpFklSuvI7UzWYVUlexiKf37ME5xeKagbz6GPtfFIvof+45LHnEl4N+vmbx5jTmGrSaNNTX2Rn4522e/5AHHL2gSJKcCBN34lGrCmlXV5fvtO3alO7edetif77Pl0r49vS057IBaUwkCnsOW/dfJbbIqYVmaWhJTYSJO/FI14SsqJ+vUq3ithMn8NDqIGG9+kHbIMePmwYY9jO0+nmmJUaX5LXjVm+OivvQhElDM/GPW2caXdjPd6BUwrfLZSz4pP017r3pdXzdaYBRNoGu/3mmJUan89pxz86c0PXQuDIbMO2XTLMJODVB9o007fqbVh6b6Lx23LMzJ8Iu5+q1kJJLaWhpL2PaasOMDqxN+2vU7Po/PD2N8pkzuoobiEvPQ1xhFx5L69qxIndImIem2cbHLi7Dm5ZWG2ZUATw6M9N0k+lm1//M6kzTNDep5vMQfaPwtK4dK3KHhHlomrXcmYYWnV/mR00FK7sfNesltXoZnFEqlU0zgpQnL89D1I1L0rp2rMg1y3LN56APTauWOwCmoYVUf98b0ye9NOtat3oZtPp93fKelhgnPJLWtXP7DqTIhFH9oGl3QVruedu8Nqo/LS3hthMn8Njp02hrWFjrrv5+PPvnP+MTL76Itz264PWzJRsHZWvX+eHpaZzxeTmnOdsyz89D3BmvaVw7Zq1oYsqofpAXSpilTU1MLTRB7Tr/29QUlhu+V3/fW13rqSuuwB0nT/rer/KZM9h+9KhnZR4k+0U3F56HKKmYUZYCjnteL8xaSZBJo/q1yTQzw8O+ezaG6e4FzfrI2zZitZdlYyUOnH3fW13rO06ebBp77V23Dn/rsaBXVmENmzczjjpgqSs8kuS1s+9uGMjExYZarYOuq7tnQkgpbX6LctWrv+9+1/rOHTuw9de/brlkb57DGs2EbeHGWaLX9HvA0IoGurpeWYjb3TMlpJSm0twcBsfHMbvs1R5f4XXfG691s+N4zf48MT8PANjV1RXrebI9PBKl8WBSeCSOJHcIyr2kN1tO8uGJs4NR3E0gbNUqPbBLxHdRqvprHSTLSGePx5XeU5SWta5es6k7ftlz9wwXdMW+MLHkqDE9L0nEsPM6UaRZemARwP4tWwJ1uYPEXqPmL3vReaysRB2Pcj0X3rxXi6VardgXpTWkY9utJFthrv9xNOMVM/3Exo24f9cunNveHus4tQaAzh6PK72nqC3rpHvNWbO79Aby63qFrZR1/eEluQej3x9Hp0jL9URsF3ep3SDHeW1+PtTGyc2YOCAfRZzGg+kDlnEwtJKCKN1BHWGLNNIiayGlThHU2qHLaL2eSK18tqcs6kop8zpO2I2Tm4laAZp2j+KkAgZJzbWV+a9gB0RpDekIW6TRCqv9cSwphe+eOoWl1d3ql1bXAwHWtvxdGXRLUtiNk1sJG1ow+R7FbVmbOmAZh1ufxlBRKmUdMb20Yti1SqdxIwW/MFCS4R5XhN04OYgwFaDJ90hXWMslbP6kIGp38N6dO3Hz5s3ojLh3ZVoL9oQJA5k0C9ZkYTdODiJoaMGWe2TzLFPdWJGnJOyGwrWu7aOnTqEIYKlaxc09PaG7tnE3Mg4iTMs/rymLYSX5Em5VAfIe2YevspSE7Q56dW2/NzODjtXjJHXeKMKEgfKcshhWVlkWvEf2YYs8ZUG6g0l0bZPuhgZt+ed9beswssqy4D2yD++IgWzM+Q3T8nc5nzcJWWRZ8B7ZhYtmGcjmRbjCyHoBImqN98gsXI/cInnp2rqedWDaZJooXL9HruDdMRS7tvYyeTINuYkVuaE46cFeJk+mITfFah6IyE0i8qKIVEVkTdyG4ovStXWhS28rWybTkFviNvGOAbgBwLc0lIUiqg1I9bS3N93Il5JnY8YR2S/WE6WUOg4A4vPgUrIaY7Hzy8sQAPVtPnbp08XJNJSF1JppIjIiImMiMnb69Om0Tuu0xh1flnF2JQ6wS5+2vGQckVlaVuQi8gsROebx33VhTqSUekgpNaSUGtq0aVP0EhMA/1isF66Pka401rdpxHGRfGvZPFBKfSSNglA4zWKxjdLs0nMCSboZR0x1JIDph9ZqtZN7TVp7EoapUPJS2acxtZ6pjgTETz+8XkQmAVwB4Kci8oSeYlErfrHYNqzs5J5Wl74myA7tlWoVB0ol9IyOYnB8HD2joy23gyN/THWkmrhZK0cAHNFUFgrJa/bn/t5e3LljB2aWllJr8QbdKJqtR72Y6kg1vMsWaxaLPbe9vcVv6xOkQtkKBKrsKTimOlINR0MckPXCRkEqFO46ox9THamGFTnFFqRCCdt6ZDpdMFmkOpJ5+MqmSBozT1qt1hh0O7ik0+lcy5jh4moEsCKnkJpVtK0qlCBL8yY1IOp6vnUWuwiRObhDkMOSaH0eKJV8W9VBK1q/ciW5M5KOchNljTsE5UhS+drlM2fw8PR07Lxlv8HZpAZEmW9NrmNF7qAgk3PCqL0Yth89ijM+PTgdmSdJpdMxY4Zcx4rcMUm0PmsvBr9KHIhe0dZnpySVTsd8a3IdR0cco3u2n9+szXpR1nPxG3y8+4ILAOjdqzRoxgyRrfgEO0Z367PVKoudEfOWW2Wn6E6n42bW5DJW5I7R3fps9mJYJ4JjQ0NYBrBQraI7YBpf0LVZdKbTMd+aXMYn2SG1tL47d+wAoKf12ezFcEFnJy4ZGwudl53lYk/MtyYX8Yl2gF+8eeqKK7SsgugVlrigsxMT8/OYr2utB524w8FHIr2YteIAv3TDO06e1LKYVi0sMTM8jPHBQbx82WWYWFg4qxIHgmfGcLEnIr1YkVsuzckutYk8by4vx87L5mJPRPqw6WO5LOLNOkIjHHzMhmuLhtEK3knLZRFv1pkZw8HHdLi+aFje8Q5aLqt4M0MjdtG9bAOZhasfOiDL1ha76uZLclVJSpff6oe8ew7IMt7M0Ij5uEmz+3j3HMJKlbwwb999jJETOY55++7jHSTKAS4a5jZW5EQ5wLx9t/FOEuUIx1HcxBi5hep31SEi4qvZIpydR0ReWJFbpNWuOkSUT7GacSJyt4j8TkR+KyJHRORcXQWjs6W5yiER2SVuf/xJALuVUu8HUALwtfhFIi9BZufZiPF+ovhihVaUUj+v++dRADfGKw75cW12nq54P9d6IdKbtXILgMf9vikiIyIyJiJjp0+f1njafHBtdl7c1fgq1SoOlEroGR3F4Pg4ekZHcaBUQsVjYSgi17WsyEXkFyJyzOO/6+p+5usAKgC+73ccpdRDSqkhpdTQpk2b9JQ+Z1xZOlZHvJ/LshK9q2UzTin1kWbfF5HPAvgYgA+rLNbEzRFXZufFXY2v9iJoXJa19iK4q7/fyutCFFWsp11ErgHwFQB/qZSa01MkasX22Xlx4/1clpXobHFj5A8A2ADgSRF5QUQe1FAmclzceL9rA79EccXNWrErOEvGiLMan849Q4lcwCeeMhE33s9lWYnexT07yWrMI6c84Z6d5CTbB36JdOCSeURElmNFTkRkOVbkRESWY0VORGQ5VuRERJZjRU5EZDlW5ERElmNFTkRkOVbkRESWY0VORGQ5VuRERJZjRU5EZDlW5ERElmNFTkRkOVbkRESWY0VORGQ5VuRERJZjRU6kyWylgtLcHGYrlayLQjnDPbKIYqpUq7h9YuKsjaD3r24E3VZgW4mSx4qcKKbbJyZwuFzGfLX6ztcOl8sAgPsHBrIqFuUImwtEMcxWKjhULmOurhIHgLlqFYfKZYZZKBWsyIlimFpcRFHE83tFEUwtLqZcIsojVuREMWzt6MCyUp7fW1YKWzs6Ui4R5RErcqIYutvasL+3F+sbBjXXFwrY39uL7jYOQ1Hy+JQRxXTvzp0AcFbWyi2rWStEaWBFThRTW6GA+wcGcFd/P6YWF7G1o4MtcUoVnzYiTbrb2jDACpwyECtGLiJ3ishvReQFEfm5iGzVVTAiIgom7mDn3Uqp9yul9gD4CYB/1FAmIiIKIVZFrpR6s+6f5wDwzsMiIqLExA7oicg/AfgMgD8DuLrJz40AGAGAvr6+uKclIqJVonwmM7zzAyK/ANDr8a2vK6X+s+7nvgagUyn1jVYnHRoaUmNjY2HLSkSUayIyrpQaWvP1VhV5iBO8F8BPlVK7A/zsaQCvajlxOBsBvJ7BeU3D67CC12EFr8MKG67De5VSmxq/GCu0IiK7lFInVv/5cQC/C/J7XgVJg4iMeb3N8obXYQWvwwpehxU2X4e4MfJ/FpH3AahipYX99/GLREREYcSqyJVSn9BVECIiiiZvi2Y9lHUBDMHrsILXYQWvwwprr4O2wU4iIspG3lrkRETOYUVORGS53FXkInK3iPxudbGvIyJybtZlyoKI3CQiL4pIVUSsTLmKQ0SuEZHfi8iEiHw16/JkQUQOi8iMiBzLuixZEZHzReQpETm++vfwxazLFEXuKnIATwLYrZR6P4ASgK9lXJ6sHANwA4Cnsy5I2kSkCOCbAK4FcDGAT4nIxdmWKhPfAXBN1oXIWAXAl5VSFwG4HMDnbXwWcleRK6V+rpSqbW1+FMC2LMuTFaXUcaXU77MuR0b2AZhQSr2slFoE8EMA12VcptQppZ4G8Mesy5ElpdS0Uuq/V///LQDHAbwn21KFl7uKvMEtAB7PuhCUuvcA+N+6f0/Cwj9e0ktEtgPYC+C5bEsSnpPbmQRZ6EtEvo6VbtX30yxbmoIueJZD4vE15uHmmIh0A3gMwJcalue2gpMVuVLqI82+LyKfBfAxAB9WDifSt7oOOTYJ4Py6f28DMJVRWShjItKOlUr8+0qp/8i6PFHkLrQiItcA+AqAjyul5rIuD2XiNwB2icgOEekA8EkA/5VxmSgDIiIADgE4rpS6J+vyRJW7ihzAAwA2AHhyda/RB7MuUBZE5HoRmQRwBYCfisgTWZcpLauD3bcBeAIrg1s/Ukq9mG2p0iciPwDwawDvE5FJEdmfdZky8AEANwP40Gp98IKIfDTrQoXFKfpERJbLY4uciMgprMiJiCzHipyIyHKsyImILMeKnIjIcqzIiYgsx4qciMhy/w9TJEsNaK3rNQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#PPT的例子不好，以下是更常用的例子\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "x = np.random.randn(100)\n",
    "y = np.random.randn(100)\n",
    "plt.scatter(x, y, marker='o', color='c', s=40, label='Point')\n",
    "\n",
    "plt.legend(loc='best')    # 设置 图例所在的位置 使用推荐位置\n",
    "\n",
    "plt.show()\n"
   ]
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